Global temperature map comparison

This new work showcases one month available for all datasets, February 2015. The image above, lower troposphere from UAH V6 beta is merely a picture, the true work is in a PDF for local display. The intent is information, not hitting you in the face, so whilst as such green is a colour few people like that is how it has turned out. New geographic map, new colours.

Like this:

There are no captions in the PDF, so (apart from HadCRUT) I cannot tell what the various maps represent. Also, some way of showing change over time would be useful, as also with the UK Met Office data, as I mentioned.

Yes you are right it ought to have identifiers. This is not as trivial as it might seem, nothing I’ve seen describes eg. the sensing layers for all different providers. Anything has to be usable here, copyright figures too.

I’ll sort something minimal out. Okay, looks like a change to the alias data would be a choice insert, pragmatically type in the couple of dozen descriptions. Twenty minutes later, it works. Needed 3 keystrokes to the main code to accept the data layout change. Add some indirection for brevity and then add a label to the plot routine, done.
Might look better swapping this for the present title text.

Oh yes, that’s better. 🙂

A bit of a problem for me is isolation, no-one to talk to or show anything. There comes a point when the best bet is publish as-is, with loose ends.

Clickable.
Lets see if WordPress have fixed the 256 colour PNG breakage.
[ Yes, good ]

The simplest means is via a huge PDF so more or less no-one would bother looking. (tried this ages ago). Minimising fidelity has to go too far. PNG/GIF animations are not controllable, large.

Video doesn’t work well, not controllable by normal viewers which are intended for film, also huge files and for this site hosting video is three upgrade levels, I’m retired.

On a different level there are serious dataset flaws. I have to bite my tongue over the universal bad practice, 19th century mathematics where Nyquist etc. is ignored.

For satellite there are woefully few, even 10x as many would still be too few. As it stands it takes several days to get surface coverage so sensing is not contiguous nor meeting basic sampling requirements. Weather also moves rapidly.

A major improvement would be contiguous publication of data by the day, not all dumped in a month, that way the gradual change would appear.

Could be that using a different projection would help. I did implement Lamaz, hit rendering problems, might or might not work. Probably needs render in stages with some plot ordering inverted. The point here is trying to put more clarity on the 180 degree view for Australasian readers and those dealing with Pacific SST.